Platform · PropertyGuru

PropertyGuru Data Scraping

New launches and resale homes are two markets with different sellers, different pricing logic and different completion dates. Pooling them describes neither.

PropertyGuru data scraping collects property listings across Southeast Asian markets. The structural split that matters most: new-launch developer projects and resale listings are different markets. Developers price new launches against a construction and sales programme; resale sellers price against comparable transactions. Pooling them produces a price series that describes neither.

The markets here also differ from each other more than a single regional feed suggests, so country is a dimension and a regional average is a figure nobody transacts at.

Get a free sample See sample data

Free pilot on your own PropertyGuru list, returned in 24 hours. No card, no trial clock — and you keep the sample data either way.

propertyguru.jsonl LIVE FEED

{"listing_id":"pg-44120","country":"SG", "listing_category":"resale", "tenure":"leasehold","tenure_years":99, "price":1280000,"price_type":"asking", "area_value":93,"area_basis":"sqm", "cluster_basis":"unit_level"} {"listing_id":"pg-88120","country":"MY", "listing_category":"new_launch", "project_name":"example project", "expected_completion":"2029-Q2", "cluster_basis":"project_level", "note":"years from handover. pooling this with resale describes neither market"} {"cluster_basis":"project_level","cluster_listing_count":47, "unit_count_in_project":"not_a_property_count", "takeup_rate":"not_produced", "caution":"a listing ending often means one agent stopped marketing, not a sale"}

3 of 1,884,220 listing rows · SEAlisting_category on every row · never pooled · schema v1.0

Independence and trademarks. Actowiz Solutions is not affiliated with, endorsed by or connected to PropertyGuru or its owners. PropertyGuru and related marks belong to their respective owners, used here only to name the publicly accessible source this service collects from.

Our Data Powers

B2C Marketplace

amazon

D2C + Marketplace

NYKAA

D2C + Marketplace

Walmart

FMCG Marketplace

udaan

Food Delivery

Uber Eats

Quick Commerce

blinkit

Taxi Aggregator

Uber

E-Commerce

Tmall

PropertyGuru at a glance

How we handle PropertyGuru specifically

Platform-specific handling, not a generic retail template pointed at a different domain.

Portal: PropertyGuru — Southeast Asian markets
The structural split: New launch versus resale. Different markets
Why: Developers price to a programme; resale sellers price to comparables
Completion: New launch may be years from handover. Not comparable to ready stock
Country: A dimension. Tenure rules and buyer restrictions differ per market
Tenure: Freehold and leasehold both common, with terms varying by country
Foreign buyers: Restrictions differ by market. Recorded where stated
Refresh: Daily. New-launch listings update on a campaign cadence

Platform specifics

Two markets, several countries

These are the reasons a PropertyGuru dataset needs its own handling rather than a shared retail schema.

New launch and resale price on different logic

A developer pricing a new launch is pricing against a construction cost base, a sales programme and a launch strategy. A resale seller is pricing against what comparable homes recently achieved.

New-launch pricing moves in steps as phases release, rather than continuously.
Resale pricing moves with the market, continuously and in both directions.
New launch may be years from completion, so the buyer is purchasing a future asset.
The two respond to interest rates and demand differently, and on different lags.

listing_category is on every record — new_launch or resale — with expected_completion where a new launch states one.

A pooled average across the two is not a market price. It is a blend whose composition shifts with the launch pipeline, so it moves for reasons that have nothing to do with the market it claims to measure.

Several countries, not one region

PropertyGuru operates across markets that differ substantially in tenure rules, buyer restrictions, price levels and currency.

Tenure conventions differ — freehold and leasehold both appear, with terms that are not equivalent across borders.
Foreign-buyer restrictions differ, and they materially affect which listings are addressable for which buyer.
Price levels differ by orders of magnitude, so a regional average is a figure nobody transacts at.

country is a dimension on every record. Cross-market comparison is a deliberate join with FX stamped per observation, and we do not produce a regional average unless you ask, in which case it arrives as a computed rollup with the country detail retained.

Foreign-buyer eligibility

Where a listing states restrictions or eligibility, we capture the text as published. We do not assess whether a specific buyer is eligible — that depends on nationality, residency status and the property's classification, which is a legal determination rather than a data one.

Duplication, developer listings, and what we do not produce

Duplication has two shapes here

Resale duplication works like the Spanish pattern — several agents, one property.
New-launch duplication is different: many agents market the same project, and individual units may or may not be distinguished.

Clustering handles both, and cluster_basis distinguishes a project-level grouping from a unit-level one. A project-level cluster is not a property count, and we label it so nobody counts a 400-unit development as one listing or as 400.

What we do not produce

Transaction prices. Asking only, on both categories.
Take-up or sell-through on a new launch. Not published, and inferring it from listing disappearance is unreliable when many agents market the same units.
Agent or buyer personal data, in any form.

The take-up point matters: a new-launch listing disappearing frequently means one agent stopped marketing, not that a unit sold.

Scope

What we collect on PropertyGuru, and what we do not

The right column matters more than the left. Anyone can list fields; the limits are what tell you whether the dataset will hold up.

✅ What we collect

listing_category on every record — new_launch or resale
expected_completion where a new launch states one
country as a dimension, with FX stamped per observation
Tenure recorded with the country, since terms are not equivalent across borders
Foreign-buyer restriction text as published, never assessed
Clustering with cluster_basis distinguishing project from unit level
Project-level clusters labelled as such, never counted as properties
price_type constant asking, on both categories
Agency name as a commercial entity

❌ What we do not, and why

A pooled average across new launch and resale
A regional average across markets that differ by orders of magnitude
An assessment of whether a specific buyer is eligible
New-launch take-up inferred from listing disappearance
Agent, buyer or any individual's personal data

Core PropertyGuru fields

The full dictionary is agreed during scoping. These are the fields specific to this platform.

Field	What it is on this platform
listing_id / country / city / district	The listing and its market
listing_category	new_launch or resale. Different markets
expected_completion	Where a new launch states one
project_name / developer_name	For new launches. Commercial entities
price / currency / price_type	Asking, with the type constant
fx_rate / fx_observed_at	For deliberate cross-market joins
tenure / tenure_years	Recorded with country, since terms differ
foreign_buyer_note	As published. Never assessed
property_cluster_id / cluster_basis	project_level or unit_level, labelled
area_value / area_basis	With the basis or flagged unstated
observed_at	Timestamp

Use cases

What teams do with PropertyGuru data

Resale market price series

Resale listings isolated from new launch, so a price series moves with the market rather than with a launch pipeline whose composition shifts independently.

New-launch pipeline tracking

Projects with expected completion and developer recorded, showing what is coming to market and when — which a pooled feed cannot separate out.

Cross-market comparison done deliberately

Country as a dimension with FX per observation, since these markets differ by orders of magnitude and a regional average is a figure nobody transacts at.

Tenure exposure by market

Tenure recorded with its country, since freehold and leasehold terms are not equivalent across borders and a pooled tenure field would be misleading.

The 24-hour sample — run on your sources, not ours

Send us a PropertyGuru item or category list. We run real collection against it and return the output within 24 hours, with the platform-specific fields populated so you can check them yourself rather than take our word for it.

Real extraction from your actual sources
Returned within 24 hours
Coverage and QA note included
You keep the data either way
No card, no trial clock
Named engineer on the call

Get my free sample Book a 20-min scoping call Reply within one business day. Reference calls available under NDA.

How we engage

Three ways to engage us

Same collection pipeline and QA underneath. The difference is who holds the schedule and how the data reaches you.

Managed service (most common)

We own the collection, the QA and the delivery. You receive clean data on a schedule and never touch a scraper.

Dedicated engineer assigned to your account
Site changes fixed by us, not reported to you
Scheduled delivery to your warehouse or S3
Named contact on Slack or email

Best fit: Teams who need the data, not the infrastructure.

API access

The same collection pipeline exposed as an authenticated REST endpoint your systems query directly.

On-demand and scheduled endpoints
Rate limits agreed to your load profile
Sandbox keys for integration testing
Versioned schema with deprecation notice

Best fit: Product and engineering teams building on live data.

One-time or project extraction

A defined pull for a specific question — market sizing, diligence, a pitch, a one-off audit.

Fixed scope agreed in writing upfront
Single delivery with full QA report
Methodology documented for your records
Converts to managed if you want continuity

Best fit: Research, strategy and diligence work with a deadline.

Pricing

Every engagement is quoted individually, because the honest answer depends on your scope: how many sources, how many records, how often, and how the data reaches you. We scope it with you, run a free pilot on your own sources, and then quote a fixed monthly figure — no per-request metering and no overage billing when volumes move. Request a quote and you will have a number after one call.

PropertyGuru is usually collected alongside its competitors

Almost nobody buys a single platform in isolation. PropertyGuru data becomes useful when it sits next to the competitor set on one schema, refreshed on one schedule, so a price index or availability comparison is genuinely like-for-like.

That is what real estate data covers, and a PropertyGuru-only engagement can be expanded into it without rebuilding. If you already know you need several platforms, start there instead — it is the same pipeline and usually the better scoping conversation.

FAQ

PropertyGuru data scraping: frequently asked questions

Platform-specific questions, including what cannot be collected here.

Because they are different markets. A developer prices a new launch against a construction cost base and a sales programme; a resale seller prices against comparable transactions.

New-launch pricing moves in steps as phases release; resale moves with the market continuously. A pooled average is a blend whose composition shifts with the launch pipeline — so it moves for reasons unrelated to the market it claims to measure.

As a computed rollup with country detail retained, if you ask. Not as a primary figure.

These markets differ by orders of magnitude in price level, and differ in tenure rules and buyer restrictions. A regional average is a number nobody transacts at.

No. We capture any stated restriction or eligibility text as published.

Whether a specific buyer qualifies depends on nationality, residency status and the property's classification — a legal determination, not a data one.

Differently from resale. On resale it is the familiar pattern of several agents marketing one property. On new launches, many agents market the same project and individual units may or may not be distinguished.

cluster_basis distinguishes project-level from unit-level grouping, and a project-level cluster is labelled so nobody counts a 400-unit development as one listing or as 400.

No. Take-up is not published, and inferring it from listing disappearance is unreliable when many agents market the same units — a listing ending frequently means one agent stopped marketing, not that a unit sold.

We quote individually. Country count is the dominant driver rather than listing volume, because each market needs its own tenure, currency and restriction handling.

One scoping call, a free pilot within 24 hours, then a fixed monthly quote. Request a quote.

See real PropertyGuru data before you commit to anything

Send us an item or category list. We return the output within 24 hours with the platform-specific fields populated.

Get a free sample Talk to an engineer

Free pilot, no card, no obligation. If we cannot collect a field you need on this platform, the sample shows you that too.

Hear It Directly from Our Clients

Watch how businesses like yours are using Actowiz data to drive growth.

▶

1 min

★★★★★

"Actowiz Solutions offered exceptional support with transparency and guidance throughout. Anna and Saga made the process easy for a non-technical user like me. Great service, fair pricing!"

Thomas Galido

Co-Founder / Head of Product at Upright Data Inc.

▶

2 min

★★★★★

"Actowiz delivered impeccable results for our company. Their team ensured data accuracy and on-time delivery. The competitive intelligence completely transformed our pricing strategy."

Iulen Ibanez

CEO / Datacy.es

▶

1:30

★★★★★

"What impressed me most was the speed — we went from requirement to production data in under 48 hours. The API integration was seamless and the support team is always responsive."

Febbin Chacko

-Fin, Small Business Owner